摘要
为了对汽车外观设计进行相对客观的评价,在分析人工神经网络原理的基础上提出了应用BP神经网络评价汽车外观设计的方法。根据BP神经网络具有自学习、自组织、自适应和非线性动态处理等优点,建立了汽车外观设计BP神经网络评价模型,选择20款汽车外观作为学习样本、8款汽车外观作为检验样本,利用MATLAB软件进行了BP网络的实例训练和验证。实验结果表明,BP神经网络模型可以较准确地对汽车外观设计进行评价。
In order to evaluate the exterior design of vehicles in a relatively objective way,the method of using BP neural network is proposed to evaluate vehicle exterior design after analyzing theory of artificial neural network.Based on the advantages of BP neural network such as self-learning,self-organization,self-adaption and nonlinear dynamic processing,a BP neural network evaluation model for vehicle exterior design was established.Twenty vehicle samples were selected as learning samples,and eight vehicle samples were used as test samples.The training and verification of the example of BP network were conducted using MATLAB software.The simulation results show that BP neural network is an efficient and accurate method to evaluate vehicle exterior design.
作者
李彦龙
蔡谦
孙久康
高想
LI Yanlong;CAI Qian;SUN Jiukang;GAO Xiang(School of Automotive Studies,Tongji University,Shanghai 201804,China;Design Department,SAIC Volkswagen Automotive Co.,Ltd.,Shanghai 201804,China)
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2021年第1期116-123,共8页
Journal of Tongji University:Natural Science
关键词
工业设计
汽车外观设计
人工神经网络
评价模型
industrial design
vehicle exterior design
artificial neural network
evaluation model
